Corporate training

AI training forteams that aren't technical.

Your people are already using AI. Most of them are using it as a search box, and nobody has shown them anything better. This is hands-on training for the departments that were never given a technical brief — operations, sales, HR, finance, marketing, admin, customer support.

Talk to us about your team How a session runs

The gap isn't tools. It's how people use them.

Most companies have bought access to AI. Far fewer have changed how any actual work gets done.

What usually happens: a handful of enthusiasts get fluent on their own, everyone else pastes in a question and takes the first answer, and a few people quietly put things into a chat window that should never have left the building. The tool arrived; the judgement didn't.

Vertura has spent its work teaching people to think with AI rather than defer to it — the same method, moved from students to working teams. Same principle underneath: minimum theory, maximum hands-on. Nobody sits through a slide deck about the history of large language models.

Six things a team leaves able to do.

The same five capabilities that run through every Vertura programme, translated into the work your team actually does — plus the one that keeps a company out of trouble.

Think with AI

Asking better questions, prompting deliberately, and knowing when the answer on screen is wrong. The single highest-leverage habit, and the one almost nobody is taught.

Research with AI

Comparing sources, testing claims, and pulling a defensible summary out of a mess of material — instead of accepting the first confident paragraph.

Create with AI

Drafts, decks, briefs, first-pass copy and visuals produced in minutes rather than afternoons, then edited by the person who owns the work.

Build with AI

Combining tools into something that runs repeatedly — a workflow, a template, a small internal utility the team actually uses after the session ends.

Solve with AI

Taking a real bottleneck from your own operation, breaking it down, and working it through with AI in the room.

Judge the output

Where AI is confidently wrong, what must never be pasted into it, and which decisions stay with a human. The part that keeps the rest safe.

Minimum theory. Maximum hands-on.

How an engagement runs.

1
A scoping call
Which teams, what they spend their week doing, and where the time actually goes. We ask for two or three real tasks — not hypotheticals — because those become the material.
2
The session is built around your work
Your documents, your processes, your bottlenecks. A finance team and a sales team leave with different outputs because they came in with different problems.
3
The team works, live
Everyone is on their own laptop doing their own task. The measure of the session is what each person produced in it, not whether they enjoyed the talk.
4
You keep what was built
The prompts, workflows and templates the team created stay with you, written down, so a new joiner in three months isn't starting from nothing.

Book a scoping call

Questions companies ask first.

Do our people need any technical background?

None. The training is built for people who have never written a line of code and never will. If someone can use email and a spreadsheet, they can do this.

Which AI tools do you teach?

The ones your company already pays for, wherever possible. The habits transfer between tools — how to frame a question, how to check an answer, when to stop trusting it — and those outlast whichever product you are on this year.

What about our confidential data?

It is part of the training rather than a disclaimer at the end. Teams work through what should never be pasted into a public tool, what your own policy allows, and how to get the benefit without putting client or employee information somewhere it cannot be retrieved from.

How long does it take?

That depends on how many teams and how deep you want to go. We agree the shape on the scoping call rather than selling a fixed package before understanding the work.

How do we know it worked?

Ask your team what they stopped doing manually. The session produces real outputs on real tasks, so the evidence is in the work rather than in a feedback form.